Method for detection of cancer based on spatial genome organization

ABSTRACT

The invention provides methods of detecting abnormal cells in a sample using the radial position of one or more genes within the nucleus of a cell, as well as a kit for detecting abnormal cells using such methods. The invention also provides methods of identifying gene markers for abnormal cells using the radial position of one or more genes within the nucleus of a cell.

CROSS REFERENCE TO RELATED APPLICATIONS

This patent application claims the benefit of U.S. Provisional PatentApplication No. 61/094,318 filed Sep. 4, 2008, which is incorporated byreference.

BACKGROUND OF THE INVENTION

Cancer is a leading cause of death worldwide. Survival rates for manycancers can be improved by early detection and treatment. Some patientsand physicians disfavor available early detection methods due toinvasiveness and/or perceptions of unreliability. More reliable methodsof early detection are desired, as are less invasive methods ofdetection.

Ideal cancer diagnostics could be used in identifying a wide range ofcancers, including solid tumor malignancies as well as hematologicalmalignancies. Diagnostics capable of detecting precancerous cells arealso desirable.

BRIEF SUMMARY OF THE INVENTION

Genes are non-randomly arranged within the cell nucleus. It has beensurprisingly found that in abnormal cells, such as in cancers, thespatial organization of the genome is altered. Specifically, in someabnormal cells, the position of a gene relative to the nuclear centerand/or the nuclear membrane, also called the radial position, differsfrom the position of the corresponding gene in a normal cell.Advantageously, detection of such difference is not limited toevaluation of mitotic chromosomes.

In an embodiment, the invention provides a method of detecting abnormalcells in a sample, the method comprising: (a) obtaining a samplecomprising one or more cells from a subject, wherein one or more cellsin the sample has a nucleus, and wherein each nucleus has a nuclearcenter and a nuclear membrane; (b) identifying the position of one ormore genes within the nucleus relative to the nuclear center and/ornuclear membrane; and (c) comparing the position of the one or moregenes with a positive and/or negative control; wherein a statisticallysignificant difference in the position of the one or more genes ascompared to a negative control, or a lack of statistically significantdifference in the position of the one or more genes as compared to apositive control indicates the presence of abnormal cells.

In another embodiment, the invention also provides a method foridentification of gene markers for abnormal cells, the methodcomprising: (a) obtaining a test sample comprising one or more abnormalcells from a subject, wherein one or more cells in the sample has anucleus, and wherein each nucleus has a nuclear center and a nuclearmembrane; (b) obtaining a control sample comprising one or more normalcells from a subject, wherein one or more cells in the sample has anucleus, and wherein each nucleus has a nuclear center and a nuclearmembrane; (c) identifying the position of one or more genes within thenucleus relative to the nuclear center and/or nuclear membrane; and (d)comparing the position of the one or more genes from the test samplewith the corresponding position of the one or more genes from thecontrol sample; and (e) determining the statistical significance of adifference in the position of the one or more genes from the test sampleas compared to the control sample; wherein a gene having a statisticallysignificant difference in position in the test sample as compared to thecontrol sample is identified as a gene marker for abnormal cells.

In another embodiment, the invention also provides a kit for detectingabnormal cells in a sample, the kit comprising: (a) a labeled DNA probefor each of one or more genes selected from the group consisting ofHES5, HSP90AA1, TGFB3, ERBB2, FRA2 (also known as FOSL2), CSF1R, MYC andAKT1; (b) instructions for measurement of the position of one or moregenes in the sample, and interpretation of the results.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 depicts P value comparisons of radial distributions of BCL2,CCND1, CSFR1, ERBB2, FRA2 (FOSL2), HES5, HEY1, TGFB3, and VEGF innon-cancerous samples N1-N5. Radial distributions were evaluated foreach of N1 and N5, and paired comparisons were made. For each pairedsample indicating P>0.01, the radial distributions were statisticallythe same at a significance of P>0.01.

FIG. 2 is a plot of the cumulative frequency (y-axis) of the radialposition (x-axis) of HES5 in an individual cancer (C) sample and anindividual normal (N) sample along with statistical comparisons of sixcancerous samples and three non-cancerous control samples.

FIG. 3 is a plot of the cumulative frequency (y-axis) of the radialposition (x-axis) of HES5 for six cancerous samples and threenon-cancerous control samples. Samples C2-C6 are depicted in a commonpositional group, while sample C1 is shown separately due to itsalignment with the control samples.

FIG. 4A is a plot of the cumulative frequency (y-axis) of the radialposition (x-axis) of AKT1 for an individual cancer sample and anindividual normal control sample along with statistical analysis ofseven cancerous samples and three non-cancerous control samples.

FIG. 4B is a plot of the cumulative frequency (y-axis) of the radialposition (x-axis) of ERBB2 for an individual cancer sample and anindividual normal control sample along with statistical analysis ofseven cancerous samples and three non-cancerous control samples.

FIG. 5 is a plot of the cumulative frequency (y-axis) of the radialposition (x-axis) of AKT1 for seven cancerous samples and threenon-cancerous control samples. Samples C3, C4, C6, and C7 are identifiedin a common positional group. Samples C1 and C2 are identified in acommon positional group. Control samples are identified as a commonpositional group. Sample C5 is identified separately due to itsalignment with the control samples.

FIG. 6 conceptually depicts radial position of a gene within a nucleusof a cell.

FIG. 7A is a plot of the cumulative frequency (y-axis) of the radialposition (x-axis) of HES5 for the tested cancerous samples (solidlines), as compared to a standardized normal (i.e., non-cancerous)distribution (dashed line).

FIG. 7B is a plot of the cumulative frequency (y-axis) of the radialposition (x-axis) of HSP90AA1 for the tested cancerous samples (solidlines), as compared to a standardized normal (i.e., non-cancerous)distribution (dashed line).

FIG. 7C is a plot of the cumulative frequency (y-axis) of the radialposition (x-axis) of MYC for the tested cancerous samples (solid lines),as compared to a standardized normal (i.e., non-cancerous) distribution(dashed line).

FIG. 7D is a plot of the cumulative frequency (y-axis) of the radialposition (x-axis) of FOSL2 for the tested cancerous samples (solidlines), as compared to a standardized normal (i.e., non-cancerous)distribution (dashed line).

DETAILED DESCRIPTION OF THE INVENTION

In one embodiment, the invention provides a method of detecting abnormalcells in a sample, the method comprising: (a) obtaining a samplecomprising one or more cells from a subject, wherein one or more cellsin the sample has a nucleus, and wherein each nucleus has a nuclearcenter and a nuclear membrane; (b) identifying the position of one ormore genes within the nucleus relative to the nuclear center and/ornuclear membrane; and (c) comparing the position of the one or moregenes with a positive and/or negative control; wherein a statisticallysignificant difference in the position of the one or more genes ascompared to a negative control, or a lack of statistically significantdifference in the position of the one or more genes as compared to apositive control indicates the presence of abnormal cells.

The one or more genes can be any genes that are differentially localizedin tumor tissue as compared to normal tissue. In preferred embodiments,the gene can be HES5, HSP90AA1, TGFB3, ERBB2, FOSL2 (also known asFRA2), CSF1R, MYC, AKT1 or any combination thereof. Each of these geneshas been previously characterized, and sequence and other information isavailable through the Online Mendelian Inheritance in Man (OMIM)database (available at www.ncbi.nlm.nih.gov/sites/entrez?db=omim).Exemplary accession numbers for preferred genes can include AL139246(HES5), M27024 (HSP90AA1), NM_(—)003239 (TGFB3), X03363 (ERBB2),NM_(—)005253 (FRA2/FOSL2), CSF1R (NM_(—)005211, NM_(—)002467 (MYC), andNM_(—)005163 (AKT1). In more preferred embodiments, at least two genesare analyzed (i.e., identified and compared) in a given sample. However,one, two, three, four, five, six, seven, eight, or more than eight genescan be analyzed according to the methods of the present invention.

In another aspect, the invention provides a method of determining aprognosis of the subject that provided the sample in which abnormalcells have been detected. The prognosis can be determined based oncomparisons of the position of one or more genes in a sample as comparedwith positions of genes in samples having known prognoses/phenotypes,i.e., positive controls, and/or positions of genes in normal samples,i.e., negative controls. In some cases, the control can be astandardized distribution of radial positions prepared by the methodsdescribed herein, pooling radial positions from samples having knownphenotypes (i.e., normal samples, cancerous samples, cancerous sampleshaving a specific prognosis, etc.). For example, the gene AKT1 indicatesa poor prognosis when it is positioned toward the nuclear membrane orperiphery as compared to a normal sample. In contrast, positioning ofAKT1 toward the nuclear center as compared with a normal sample isassociated with a good prognosis.

In yet another aspect, the invention provides a method foridentification of gene markers for abnormal cells, the method comprising(a) obtaining a test sample comprising one or more abnormal cells from asubject, wherein one or more cells in the sample has a nucleus, andwherein each nucleus has a nuclear center and a nuclear membrane; (b)obtaining a control sample comprising one or more normal cells from asubject, wherein one or more cells in the sample has a nucleus, andwherein each nucleus has a nuclear center and a nuclear membrane; (c)identifying the position of one or more genes within the nucleusrelative to the nuclear center and/or nuclear membrane; (d) comparingthe position of the one or more genes from the test sample with thecorresponding position of the one or more genes from the control sample;and (e) determining the statistical significance of a difference in theposition of the one or more genes from the test sample as compared tothe control sample; wherein a gene having a statistically significantdifference in position in the test sample as compared to the controlsample is identified as a gene marker for abnormal cells. In somepreferred embodiments, (a)-(e) can be repeated using multiple testand/or control samples, and the resulting data pooled to provide aprofile of radial positions for the one or more genes, which profile canbe used as a control or a diagnostic, as shown, for example, in FIGS.7A-7D. In more preferred embodiments, the multiple test and/or controlsamples are obtained from multiple subjects.

In the methods of the present invention, the abnormal cells can be anyabnormal cells. Preferably, the abnormal cells are cells associated witha cancer or cancer related condition. For example, the cells can besolid tumor cells, hematologically malignant cells, benign cells, atypiccells, dysplastic cells, transformed cells, metastatic cells,non-infiltrating malignant cells, infiltrating malignant cells,premalignant cells, neoplastic cells, cancer stem cells, or anycombination thereof, before or after a treatment has been administered.The cancer can be any cancer, including but not limited to renal cellcarcinoma, hepatocellular carcinoma, cervical cancer, melanoma, thyroidcarcinoma, malignant gliomas, breast cancer, colon cancer, lung cancer,pancreatic cancer, prostate cancer, stomach cancer, ovarian cancer,testicular cancer, Kaposi's sarcoma, bone cancer, B-cell lymphomas,chronic lymphocytic leukemia, acute lymphocytic leukemia, Non-Hodgkin'slymphomas, multiple myeloma, acute myelocytic leukemia, and chronicmyelocytic leukemia. In another embodiment, the abnormal cells have amorphology associated with Hutchinson-Gilford Progeria.

The position of the one or more genes within the nucleus can beidentified using fluorescence in situ hybridization (FISH) as describedherein or using commercial FISH protocols and reagents readily availableto one of ordinary skill in the art. Other methods of identifying theposition of a gene in a nucleus known to one of ordinary skill in theart would also be useful in the present invention.

The position of the one or more genes within the nucleus can beidentified as a percentage of the nuclear radius, i.e., the distancefrom the nuclear center to the nuclear membrane, also called the radialposition. The nuclear center can represent 0% distance, with the nuclearmembrane representing 100% distance, or alternatively, the nuclearmembrane can represent 0% distance, with the nuclear center representing100% distance. See e.g., FIG. 6. However, any other computation capableof expressing the position of a gene relative to the nuclear membranecan also be used. For example, in some embodiments the position may bemeasured in terms of the closest distance from the gene to the nuclearmembrane, which can be measured in absolute terms, relative to theaverage nuclear radius, relative to the shortest nuclear radius, orrelative the longest nuclear radius.

Samples for use in the methods of the present invention can be taken byany method capable of collecting cells comprising nuclei. For example,the sample can be obtained using a needle biopsy. In other embodiments,the sample can be obtained from a surgical or open biopsy. One advantageof the present invention is that samples used can be smaller thanconventional biopsy samples. In a preferred embodiment, a portion of asample obtained using a needle biopsy or surgical biopsy can be used inthe methods of the present invention, while another portion of the samesample can be used in conventional diagnostic and/or prognostic methods,thereby decreasing the need for costly and/or invasive procedures in thesubject. Samples can comprise a relatively small number of cells, suchas about 100-250 cells. In some cases, samples can comprise fewer thanabout 100 cells, about 100 cells, at least 100 cells, or more than 100cells such as 150, 200, 250, or more than 250 cells. It will beunderstood that the precise number of cells is not limiting. In apreferred embodiment, the sample comprises at least about 100 cells. Ina more preferred embodiment, the sample comprises about 100-230 cells.

The subject can be a human or any suitable non-human mammal such as amouse, rat, rabbit, cat, dog, pig, sheep, cow, or primate. In someembodiments, the subject is an animal used in a non-human experimentalanimal model, such as a mouse. In a preferred embodiment, the subject isa primate. In a more preferred embodiment, the subject is a human.

In determining statistical significance in the methods of the presentinvention, one of ordinary skill in the art can readily undertake therelevant calculations. Preferably, measurements will be determined at asignificance of P<0.01. In other embodiments, measurements can bedetermined at a significance of P<0.05 or P<0.10. The rate of falsepositives and/or false negatives associated with measurement of radialposition can vary by gene. For a false positive, a gene has astatistically significant (1-D KS-test, P<0.01) difference in radialposition in a non-cancerous sample compared to that of the pooled normaldistribution. A non-cancerous sample can be from any non-canceroustissue such as normal tissue in the absence of cancer, normal tissueadjacent to cancerous tissue, and breast tissue with the non-cancerousbreast diseases such as fibroadenoma and hyperplasia. For a falsenegative, a gene has a statistically similar radial position in acancerous sample compared to that of the pooled normal distribution.Table 1 provides a listing of false positive and false negative rates bygene for HES5, HSP90AA1, TGFB3, ERBB2, FOSL2 (also known as FRA2),CSF1R, MYC, and AKT1.

TABLE 1 Gene False negatives False positives HES5 0/13 (0%) 1/12 (8.3%)HSP90AA1 2/11 (18%) 2/11 (18%) TGFB3 3/14 (21%) 0/13 (0%) MYC 3/11 (27%)0/11 (0%) ERBB2 4/14 (29%) 4/14 (29%) FOSL2 4/13 (31%) 0/12 (0%) CSF1R4/13 (31%) 0/12 (0%) AKT1 5/14 (35%) 1/12 (8.3%)

In yet another aspect, the invention provides a kit for detectingabnormal cells in a sample, the kit comprising: (a) a labeled DNA probefor each of one or more genes selected from the group consisting ofHES5, HSP90AA1, TGFB3, ERBB2, FOSL2 (also known as FRA2), CSF1R, MYC,and AKT1; and (b) instructions for measurement of the position of one ormore genes in the sample, and interpretation of the results. The DNAprobe can be prepared using known gene sequences for the identifiedgenes and any suitable commercially available DNA labeling product.

The following examples further illustrate the invention but, of course,should not be construed as in any way limiting its scope.

Example 1

This example demonstrates the identification of a set of gene markersfor the detection of tumor cells.

Normal and cancerous human breast tissue samples were obtained from theAIDS and Cancer Specimen Resource (ACSR), Univ. California San Francisco(UCSF), San Francisco, Calif., BioChain Institute, Inc., Hayward,Calif., Capital Biosciences, Inc, Rockville, Md., Imgenex Corp., SanDiego, Calif. and US Biomax, Inc, Rockville, Md. Samples N1 through N11were identified by the source in materials accompanying the samples asnormal, i.e., non-cancerous. Samples C1 through C15 were identified ascancerous.

Samples of the tissue are prepared as formalin fixed paraffin embedded(FFPE) or FFPE tissue microarrays (TMAs). Each sample is subjected tofluorescence in situ hybridization (FISH) for twenty genes: AKT1, CSF1R,FRA2 (FOSL2), HES5, HSP90AA1, ERBB2, MYC, HES1, HEY1, MMP1/3/12, TGFB3,VEGF, ZNF217, BCL2, BRCA1, CCND1, PTGS2, PTEN, TLE, and TJP-1 (asidentified in OMIM/Entrez gene).

Preparation of samples: Samples are de-paraffinated using xylene(Mallinckrodt Chemicals). A dehydrating series of ethanol at100%-90%-70% ethanol (1×5 minutes for each) is performed, followed by 10minutes hydration using PBS. Slides are boiled in 0.01M citrate buffer(700 ml) with a microwave for 10 minutes in 1000 watt microwave at fullpower (Antigen retrieval step). The samples are allowed to cool to ˜37°C. Next, 10 μg/ml RNase A (Sigma)/2×SSC is added for 15 minutes at 37°C. at 1:10,000 dilution of stock, followed by 5 min PBS. One hundred μLper slide of 0.25 mg/ml proteinase K (Sigma)/2×SSC (1:100 dil 25 mg/mlstock, 1:80 dil 20 mg/ml stock) is incubated in a humidified chamber at37° C. for: 10 minutes breast cancer sections, 11 minutes for normalbreast sections, and 10 minutes 30 seconds breast TMA. Samples arequickly rinsed in PBS, followed by a dehydration ethanol series at70%-90%-100% ethanol 1×5 minutes for each. Samples are then left to airdry.

FISH protocol: Probes are prepared using: 600-800 ng biotin (Roche)and/or digoxigenin (Roche) labeled nick translation product(commercially available probe DNA for each of the 20 genes), 10 μg humanCot1 (10 μl of 1 μg/μl stock; Roche Applied Science), 40 μg tRNA (4 μkof 10 mg/ml stock; Sigma), 1/10th volume 3M sodium actetate pH5.2, and2× volume ice cold 100% ethanol. Probes are micro-centrifuged at maxspeed (˜14,000 rpm) 20-25 minutes, at 4° C. The ethanol solution isdecanted, and the probe is dried (air dry or using speed vac (medium,approx 10 min). The probe is resuspended in 10 μl hybridization buffer(10% dextran sulfate/50% formamide/2×SSC/1% Tween20), and allowed torest for at least 30 minutes at room temperature. Probes are applied totissue slides or TMA and covered with a coverslip, which is sealed.Probe and nuclei are co-denatured at 85° C. for 10 minutes and left tohybridize overnight at 37° C. in a humidified chamber. The followingday, the coverslip is removed by removing the sealant and incubating in2×SSC for 5 minutes with aggregation. Slides are washed 3× for 5 minutesin 50% formamide (Sigma)/2×SSC at 45° C., and 3× for 5 minutes in 1×SSCat 60° C. Blocking is done using 3% BSA (Sigma)/4×SSC/0.1% Tween20 for15 minutes at room temperature. Slides are incubated with detectionreagents, which have been diluted in blocking buffer, for 2 hours at 37°C. (1:200 anti-digoxigenin-rhodamine, 1:200 fluorescein-avidin DN, bothVector Laboratories). Slides are washed in 4×SSC/0.1% Tween 20 for 3×5minutes at room temperature. Slides are counterstained and mounted withVectashield/DAPI (Vector Laboratories). Slides are stored at 4° C. untilviewed on microscope.

Imaging: Slides are imaged using an Olympus IX70 microscope (DeltavisionSystem) fitted with a CoolSnap CCD camera using a 60×, 1.4 oil objectivelens and an auxiliary magnification of 1.5 and using an optical stepsize of 0.2 μm. The thickness of the optical section is 0.5 μm.2D-maximal projections of entire imaging stacks are generated foranalysis of FISH signal positioning.

The focal planes cover the entire nucleus. The number of sections variesdepending on nucleus size. For breast tissue containing nuclei of 3-9 μmin diameter typically ˜25 sections were acquired when imaging on theOlympus Deltavision system. Typically 100-230 nuclei are analyzed pergene probe.

Analysis: For the quantitative analyses of FISH signal distributions,software generated by S. Lockett and P. Gudla (National CancerInstitute, Frederick/SAIC—Frederick Inc., MD) is used. Initially imageswere contrast-enhanced based on visual inspection and individual cellnuclei from the blue color channel were manually delineated using thePhotoshop™ program. Analysis of the red and green channels containingthe signals from FISH labels was automatic as described in Meaburn etal., J. Cell Biol. 180(1): 39-50 (2008). For the automatic detection ofFISH signals a three-stage process is used, involving: (i) noisereduction, (ii) segmentation and (iii) post-processing. (i) Backgroundnoise is removed in each channel by applying an adaptive non-linearnoise reduction technique (“SUSAN”, Smith and Brady, Int'l. J. ComputerVision 23:45-78 (1997)). (ii) A fuzzy-C-means clustering algorithm isapplied on the noise-reduced images to probabilistically assign eachimage picture element (pixel) into two classes. The two classescorrespond to background and objects in the image. The images from thisprocess are segmented into binary images whereby each pixel with morethan 50% probability of being in the object class is classified ascorresponding to actual objects in the sample, while the remainingpixels are classified as background. The integrated intensities of eachgroup of contiguous object pixels are calculated and those groups thatexceed a threshold integrated intensity, which are calculatedautomatically by the isodata threshold method in DIPimage, areconsidered to correspond to individual FISH signals. Manual comparisonhas previously demonstrated successful identification of more than 99%of FISH signals and a false positive rate of less than 1% in a studyusing cultured cells (Takizawa and Misteli, Genes & Development, 22,489-498 (2008)).

For quantification of FISH signal spatial distributions the followingnovel procedure was employed. For nuclei, the Euclidean distancetransform (DT) is computed, where the value assigned to each pixel in anucleus equals the shortest distance to the edge of the nucleus. Thesevalues are normalized for each nucleus such that the maximum DT value is1.0. For each FISH signal the position of the intensity gravity centeris determined and the DT value for that position is used to determinethe relative radial position (RRP) of each signal.

For statistical analysis to combine the RRPs of FISH signals acrossmultiple nuclei of the same sample, the cumulative distribution of RRPsis generated. Cumulative distributions from different samples arecompared using the 1D Kolmogorov-Smirnov (KS) test and differences areconsider significant if there is less than 1% probability that the twocumulative distributions arose from the same parent distribution. Pilotexperiments have previously demonstrated high reproducibility betweenrepeat experiments with variation of less than 4% of each data value. Pvalues between repeat experiments were always more than 5%. Analysistools are implemented using custom software written in MATLAB(Mathworks, Inc) with DIPImage toolbox (Technical University of Delft).

The relative distance of the signal between the nuclear center and thenuclear membrane, called the “radial position,” of each FISH signal isdetermined, and data are aggregated.

Results: Results showed little variation among control tissues in mostcases. For the gene AKT1, radial positions of samples N2, N3, N4, and N5had a consistent distribution among individuals, with P>0.01. As shownin FIG. 1, similar results were also found for BCL2, CCND1, CSFR1,ERBB2, FRA2 (FOSL2), HES5, HEY1, TGFB3, and VEGF. Most control samples,evaluated in pairs against each other, were similar to a level ofP>0.01, although in analysis of ERBB2, sample N5 showed P<0.01 withrespect to all other tested samples.

When radial positions of cancer (C) samples were compared with control(N) samples, several genes showed distinction between cancer samples andcontrol samples. In analysis of HES5, aggregated data of 5/6 cancersamples (C2-C6) showed increased location toward the periphery (nuclearmembrane) as compared to control samples (FIG. 2). In analysis of AKT1and ERBB2, aggregated data of 6/7 and 4/7 cancer samples, respectively,showed increased location toward the periphery as compared to controlsamples (FIG. 4).

When samples C1-C7 were quantified with respect to radial position ofthe twenty genes listed above, each sample had a different set of genesrepositioned as compared to every other sample, as shown in Table 2below. Radial positioning analysis of two genes, AKT1 and HES5, whenconsidered in combination, correctly indicated cancer in all sevencancer samples. That is, for each sample, radial position of at leastone of the two genes indicated cancer.

TABLE 2 Sample % genes repositioned Cancer 1 20% (3/15) Cancer 2 29%(4/14) Cancer 3 70% (7/10) Cancer 4 78% (7/9) Cancer 5 20% (2/10) Cancer6 70% (7/10) Cancer 7 53% (9/17)

Of the twenty genes considered, at least eight of the genes were foundto have radial positions useful in diagnostics: HES5, HSP90AA1, TGFB3,ERBB2, FOSL2(FRA2), CSF1R, MYC and AKT1. Table 3 below depicts P-valuesof the radial positions for these genes in 14 cancer samples (C1-C15)and Table 4 below depicts P-values of radial positions for these genesin 11 normal, non-cancerous samples (N1-N11). In Tables 3 and 4,“Mid-High” (P<0.01), and “High” (P<0.001) denote significantly differentradial positions; “Low” (P>0.05) and “Mid-Low” (0.01<P<0.05) denotestatistically similar distributions; n.d.=not determined.

TABLE 3 C#* HES5 HSP90AA1 TGFB3 MYC ERBB2 FOSL2 CSF1R AKT1 2 High Mid-Low n.d. High Low Mid- High <1 × 10⁻⁶ High 0.281  3 × 10⁻⁶ 0.516 High4.4 × 10⁻⁴ 0.0042  0.0079 3 High High High High Mid- High High High <1 ×10⁻⁶  <1 × 10⁻⁶ 4.6 × 10⁻⁴  <1 × 10⁻⁶ High <1 × 10⁻⁶  4 × 10⁻⁶ 1.7 ×10⁻⁴  0.0012 4 High High High High High n.d. n.d. High <1 × 10⁻⁶  <1 ×10⁻⁶ <1 × 10⁻⁶ <1 × 10⁻⁶ <1 × 10⁻⁶ 1.6 × 10⁻⁵ 5 High High High Low LowMid- Low Low <1 × 10⁻⁶ 7.0 × 10⁻⁵ 6.1 × 10⁻⁴  0.860 0.060 Low 0.1900.513 0.028 6 High n.d. Mid- n.d. Mid- High Mid- High <1 × 10⁻⁶ HighHigh <1 × 10⁻⁶ Low  5 × 10⁻⁶ 0.0021  0.0043 0.025 7 n.d. n.d. High n.d.High High High High <1 × 10⁻⁶ <1 × 10⁻⁶ <1 × 10⁻⁶ <1 × 10⁻⁶  <1 × 10⁻⁶ 8High High High High High Mid- High Low <1 × 10⁻⁶ 2.2 × 10⁻⁴ <1 × 10⁻⁶ <1× 10⁻⁶ <1 × 10⁻⁶ High <1 × 10⁻⁶ 0.282  0.0066 9 High High High High HighHigh High High <1 × 10⁻⁶  7 × 10⁻⁶ <1 × 10⁻⁶ <1 × 10⁻⁶ <1 × 10⁻⁶ <1 ×10⁻⁶ <1 × 10⁻⁶ 2.1 × 10⁻⁵ 10 High Low High High High Low High Low <1 ×10⁻⁶ 0.094  8.9 × 10⁻⁴  <1 × 10⁻⁶ <1 × 10⁻⁶ 0.077  4 × 10⁻⁶ 0.064 11Mid- High Mid- Mid- Low High Low High High 1.3 × 10⁻⁵ High Low 0.242  3× 10⁻⁶ 0.095  <1 × 10⁻⁶ 0.0013 0.0039 0.019 12 High Mid- High High HighHigh High High <1 × 10⁻⁶ High  7 × 10⁻⁶ <1 × 10⁻⁶ 3.4 × 10⁻⁴  1.3 ×10⁻⁴  <1 × 10⁻⁶ 8.8 × 10⁻⁴ 0.0071 13 Mid- Mid- Low High High High HighLow High Low 0.987  <1 × 10⁻⁶ <1 × 10⁻⁶ <1 × 10⁻⁶ 5.2 × 10⁻⁴  0.3840.0012 0.049  14 High Mid- Mid- High Low Low Mid- Low 2.6 × 10⁻⁵  HighHigh <1 × 10⁻⁶ 0.063 0.424 Low 0.143 0.0070 0.0073 0.019 15 High n.d.Low Low Low High High High <1 × 10⁻⁶ 0.099  0.364 0.067 <1 × 10⁻⁶ <1 ×10⁻⁶  <1 × 10⁻⁶ *C# = Cancer sample

TABLE 4 N#* HES5 HSP90AA1 TGFB3 MYC ERBB2 FOSL2 CSF1R AKT1 1  Low** LowLow Low Low Low Low Low 0.766 0.220 0.633 0.949 0.767 0.915 0.390 0.5962 Low Low n.d. n.d. n.d. Low Low n.d. 0.498 0.997 0.285 0.058 3 Low LowLow Low Mid- n.d. n.d. Mid- 0.954 0.914 0.151 0.276 Low Low 0.022 0.0374 n.d. n.d. n.d. n.d. Low n.d. n.d. n.d. 0.342 5 Low n.d. Low Low LowLow Low Mid- 0.969 0.701 0.998 0.555 0.112 0.917 High  0.0014 6 n.d.n.d. Low Low Low n.d. Low N/A 0.353 0.325 0.981 0.315 7 n.d. Low n.d.n.d. n.d. Low n.d. n.d. 0.967 0.656 8 Low Low Low Low Low Low Low Low0.763 0.081 0.543 0.178 0.129 0.579 0.158 0.144 9 n.d. n.d. Low n.d. Lown.d. n.d. Low 0.673 0.510 0.873 10 Low Low Low 0.694 Low Low Low Low0.116 0.889 0.133 0.995 0.062 0.083 0.924 11 Low n.d. Low n.d. Mid- LowLow Low 0.133 0.297 High 0.687 0.569 0.652  0.0011 *N# = Normal, i.e.,non-cancerous sample

Five of the genes were identified as having small repositioning events:HES1, HEY1, MMP1/3/12, VEGF, and ZNF217. The remaining seven genes werefound either not to be repositioned in cancer as compared to normalcells, or to have limited repositioning in a minority of samples: BCL2,BRCA1, CCND1, PTGS2, PTEN, TLE, and TJP-1. Differences in radialposition were not associated with aneuploidy.

These results demonstrate that gene markers for cancerous cells can beidentified using radial position.

Example 2

This example demonstrates the use of spatial gene positioning analysisin vitro to correlate prognosis in a subject to radial position of agene.

FISH imaging and analysis were carried out as described in Example 1with respect to cancerous samples C1-C7 and control samples N1-N5.Aggregated analysis showed that HES5 positioning was highly correlatedamong cancerous samples C2-C6, and highly correlated among controlsamples N1-N5, as shown in FIG. 3. However, individual analysis of C1-C6as compared to control (N) samples showed that the radial position ofHES5 in C1 was aligned with the control samples (FIG. 3). The phenotypeof the cancer of C1 was separately described as less aggressive thanC2-C6 in materials accompanying the tissue samples, which were providedby ACSR (UCSF, San Francisco, Calif.)

In analysis of AKT1 positioning, several cancerous samples (C3, C4, C6,C7) showed increased location toward the periphery as compared to thecontrol samples (FIG. 5). These samples were identified as havingaggressive phenotypes, i.e., poor prognosis. Other cancerous samples(C1, C2) showed increased location toward the nuclear center as comparedto the control samples. These samples were identified as having lessaggressive phenotypes, i.e., good prognosis. Sample C5 showed similarlocation as compared to the control samples, with respect to AKT1. Inmaterials provided by ACSR (UCSF, San Francisco, Calif.) accompanyingthe cell samples, it was noted that sample C5 had well characterizedcellular markers of both good (estrogen receptor positive andprogesterone receptor positive) and poor prognosis (Epidermal growthfactor receptor 2 positive).

These results show that radial position of a gene in a sample canprovide basis for prognosis, based on comparison with negative controlsand samples having known phenotypes.

Example 3

This example demonstrates the use of spatial gene positioning analysisto diagnose cancer in a patient.

A first sample is obtained from a patient A using a needle biopsy. Asecond sample is obtained from patient B using a needle biopsy. The twosamples are prepared and evaluated as described in Example 1, usingHES5, HSP90AA1, TGFB3, ERBB2, FOSL2 (FRA2), CSF1R, MYC and AKT1 or asubset of at least two of these genes. The radial position of eachselected gene is evaluated using FISH, and compared to a non-cancerouscontrol sample. The radial position of each selected gene is thencompared to a positive control, such as a cancerous sample or a profileof radial positions previously prepared. For example, the profile can bea standardized distribution of the gene in the analyzed tissuepreviously generated by pooling gene positioning data from a large pool(typically 10-20 tissue samples) of normal tissues.

For the sample taken from patient A, the radial position of at least oneof the selected genes in the sample is statistically significantlydifferent from the position of the corresponding genes of thenon-cancerous sample, i.e., negative control. For the sample taken frompatient B, the radial position of at least one of the selected genes isfound to be similar to that of the positive control.

These results indicate a diagnosis of cancer, which is able to beconfirmed by standard cancer diagnostics.

All references, including publications, patent applications, andpatents, cited herein are hereby incorporated by reference to the sameextent as if each reference were individually and specifically indicatedto be incorporated by reference and were set forth in its entiretyherein.

The use of the terms “a” and “an” and “the” and similar referents in thecontext of describing the invention (especially in the context of thefollowing claims) are to be construed to cover both the singular and theplural, unless otherwise indicated herein or clearly contradicted bycontext. The terms “comprising,” “having,” “including,” and “containing”are to be construed as open-ended terms (i.e., meaning “including, butnot limited to,”) unless otherwise noted. Recitation of ranges of valuesherein are merely intended to serve as a shorthand method of referringindividually to each separate value falling within the range, unlessotherwise indicated herein, and each separate value is incorporated intothe specification as if it were individually recited herein. All methodsdescribed herein can be performed in any suitable order unless otherwiseindicated herein or otherwise clearly contradicted by context. The useof any and all examples, or exemplary language (e.g., “such as”)provided herein, is intended merely to better illuminate the inventionand does not pose a limitation on the scope of the invention unlessotherwise claimed. No language in the specification should be construedas indicating any non-claimed element as essential to the practice ofthe invention.

Preferred embodiments of this invention are described herein, includingthe best mode known to the inventors for carrying out the invention.Variations of those preferred embodiments may become apparent to thoseof ordinary skill in the art upon reading the foregoing description. Theinventors expect skilled artisans to employ such variations asappropriate, and the inventors intend for the invention to be practicedotherwise than as specifically described herein. Accordingly, thisinvention includes all modifications and equivalents of the subjectmatter recited in the claims appended hereto as permitted by applicablelaw. Moreover, any combination of the above-described elements in allpossible variations thereof is encompassed by the invention unlessotherwise indicated herein or otherwise clearly contradicted by context.

1-15. (canceled)
 16. A method of detecting abnormal cells in a sample,the method comprising: (a) obtaining a sample comprising one or morecells from a subject, wherein one or more cells in the sample has anucleus, and wherein each nucleus has a nuclear center and a nuclearmembrane; (b) identifying the position of one or more genes within thenucleus relative to the nuclear center and/or nuclear membrane; and (c)comparing the position of the one or more genes with a positive and/ornegative control; wherein a statistically significant difference in theposition of the one or more genes as compared to a negative control, ora lack of statistically significant difference in the position of theone or more genes as compared to a positive control indicates thepresence of abnormal cells.
 17. The method of claim 16, wherein the oneor more genes are selected from the group consisting of HES5, HSP90AA1,TGFB3, ERBB2, FOSL2(FRA2), CSF1R, MYC and AKT1.
 18. The method of claim16 wherein the abnormal cells are selected from the group consisting ofsolid tumor cells, hematologically malignant cells, benign cells, atypiccells, dysplastic cells, transformed cells, metastatic cells,non-infiltrating malignant cells, infiltrating malignant cells,premalignant cells, neoplastic cells, cancer stem cells,Hutchinson-Gilford Progeria cells, or any combination thereof.
 19. Themethod of claim 17, wherein the abnormal cells are selected from thegroup consisting of solid tumor cells, hematologically malignant cells,benign cells, atypic cells, dysplastic cells, transformed cells,metastatic cells, non-infiltrating malignant cells, infiltratingmalignant cells, premalignant cells, neoplastic cells, cancer stemcells, Hutchinson-Gilford Progeria cells, or any combination thereof.20. The method of claim 16, further comprising determining a prognosisof the subject that provided the sample in which abnormal cells havebeen detected.
 21. The method of claim 17, further comprisingdetermining a prognosis of the subject that provided the sample in whichabnormal cells have been detected.
 22. The method of claim 16, whereinthe sample is obtained using a needle biopsy.
 23. The method of claim17, wherein the sample is obtained using a needle biopsy.
 24. The methodof claim 16, wherein the control is a standardized distribution profileof the position of the one or more genes.
 25. The method of claim 17,wherein the control is a standardized distribution profile of theposition of the one or more genes.
 26. A method for identification ofgene markers for abnormal cells, the method comprising: (a) obtaining atest sample comprising one or more abnormal cells from a subject,wherein one or more cells in the sample has a nucleus, and wherein eachnucleus has a nuclear center and a nuclear membrane; (b) obtaining acontrol sample comprising one or more normal cells from a subject,wherein one or more cells in the sample has a nucleus, and wherein eachnucleus has a nuclear center and a nuclear membrane; (c) identifying theposition of one or more genes within the nucleus relative to the nuclearcenter and/or nuclear membrane; (d) comparing the position of the one ormore genes from the test sample with the corresponding position of theone or more genes from the control sample; and (e) determining thestatistical significance of a difference in the position of the one ormore genes from the test sample as compared to the control sample;wherein a gene having a statistically significant difference in positionin the test sample as compared to the control sample is identified as agene marker for abnormal cells.
 27. The method of claim 26, furthercomprising repeating (a)-(e) using multiple test and/or control samples.28. The method of claim 27, wherein the multiple test and/or controlsamples are obtained from multiple subjects.
 29. The method of claim 26,wherein the abnormal cells are solid tumor cells, hematologicallymalignant cells, benign cells, atypic cells, dysplastic cells,transformed cells, metastatic cells, non-infiltrating malignant cells,infiltrating malignant cells, premalignant cells, neoplastic cells,cancer stem cells, Hutchinson-Gilford Progeria cells, or any combinationthereof.
 30. The method of claim 26, wherein the sample comprises atleast about 100 cells.
 31. The method of claim 30, wherein the samplecomprises about 100 to about 230 cells.
 32. The method of claim 26,wherein the sample is obtained from a mammal.
 33. The method of claim32, wherein the mammal is a human.
 34. A kit for detecting abnormalcells in a sample, the kit comprising: (a) a labeled DNA probe for eachof one or more genes selected from the group consisting of HES5,HSP90AA1, TGFB3, ERBB2, FOSL2, CSF1R, MYC and AKT1; (b) instructions formeasurement of the position of one or more genes in the sample, andinterpretation of the results.